… Therefore, this article provides a detailed study of machine learning applications on epileptic
seizure detection and other related knowledge discovery tasks. In this review, the collected …

… of not being able to detect the onset of a seizure, as it was not within … machine learning to
classify EEG signals into non-seizure and seizure events, and to detect the presence of seizure …

… The aim of this study is to establish a hybrid model for epileptic seizure detection with …
machines (SVMs) for classification of EEG data. SVMs are one of the robust machine learning …

… 2 Previous approaches for epileptic seizure detection This section discusses previously
proposed machine learning-based approaches for epileptic seizure detection. The rationale is to …

… seizure detection are time-consuming. Recently, several automated seizure detection
frameworks using machine learning … The two basic steps involved in machine learning are feature …

… presents a supervised machine learning approach that classifies seizure and non-seizure
records using an open dataset containing 342 records (171 seizures and 171 non-seizures). …

… Preliminary seizure detection and prediction algorithms were patient-specific, where the …
automated seizure detection system which can classify seizures and nonseizures signals. EEG …

… seizure detection based on time-frequency analysis and artificial neural networks.comput.intell.nuerosci.,80510.
[16]. Kumar,Y.,Dewal,ML,Anand,RS,2014.epileptic seizures detection in …

… This paper presents a novel method for automatic epileptic seizure detection. An optimized
… learning machine (ELM) to identify the EEG signals regarding the existence of seizure or not. …

… Kumar and MH Kolekar, “Machine learning approach for epileptic seizure detection using
wavelet analysis of EEG signals,” in Medical Imaging, m-Health and Emerging Communication …